/// <summary> /// Multiplies two matrices and updates another with the result. <c>c = alpha*op(a)*op(b) + beta*c</c> /// </summary> /// <param name="transposeA">How to transpose the <paramref name="a"/> matrix.</param> /// <param name="transposeB">How to transpose the <paramref name="b"/> matrix.</param> /// <param name="alpha">The value to scale <paramref name="a"/> matrix.</param> /// <param name="a">The a matrix.</param> /// <param name="rowsA">The number of rows in the <paramref name="a"/> matrix.</param> /// <param name="columnsA">The number of columns in the <paramref name="a"/> matrix.</param> /// <param name="b">The b matrix</param> /// <param name="rowsB">The number of rows in the <paramref name="b"/> matrix.</param> /// <param name="columnsB">The number of columns in the <paramref name="b"/> matrix.</param> /// <param name="beta">The value to scale the <paramref name="c"/> matrix.</param> /// <param name="c">The c matrix.</param> public virtual void MatrixMultiplyWithUpdate(Transpose transposeA, Transpose transposeB, Complex alpha, Complex[] a, int rowsA, int columnsA, Complex[] b, int rowsB, int columnsB, Complex beta, Complex[] c) { int m; // The number of rows of matrix op(A) and of the matrix C. int n; // The number of columns of matrix op(B) and of the matrix C. int k; // The number of columns of matrix op(A) and the rows of the matrix op(B). // First check some basic requirement on the parameters of the matrix multiplication. if (a == null) { throw new ArgumentNullException("a"); } if (b == null) { throw new ArgumentNullException("b"); } if ((int) transposeA > 111 && (int) transposeB > 111) { if (rowsA != columnsB) { throw new ArgumentOutOfRangeException(); } if (columnsA*rowsB != c.Length) { throw new ArgumentOutOfRangeException(); } m = columnsA; n = rowsB; k = rowsA; } else if ((int) transposeA > 111) { if (rowsA != rowsB) { throw new ArgumentOutOfRangeException(); } if (columnsA*columnsB != c.Length) { throw new ArgumentOutOfRangeException(); } m = columnsA; n = columnsB; k = rowsA; } else if ((int) transposeB > 111) { if (columnsA != columnsB) { throw new ArgumentOutOfRangeException(); } if (rowsA*rowsB != c.Length) { throw new ArgumentOutOfRangeException(); } m = rowsA; n = rowsB; k = columnsA; } else { if (columnsA != rowsB) { throw new ArgumentOutOfRangeException(); } if (rowsA*columnsB != c.Length) { throw new ArgumentOutOfRangeException(); } m = rowsA; n = columnsB; k = columnsA; } if (alpha.IsZero() && beta.IsZero()) { Array.Clear(c, 0, c.Length); return; } // Check whether we will be overwriting any of our inputs and make copies if necessary. // TODO - we can don't have to allocate a completely new matrix when x or y point to the same memory // as result, we can do it on a row wise basis. We should investigate this. Complex[] adata; if (ReferenceEquals(a, c)) { adata = (Complex[]) a.Clone(); } else { adata = a; } Complex[] bdata; if (ReferenceEquals(b, c)) { bdata = (Complex[]) b.Clone(); } else { bdata = b; } if (beta.IsZero()) { Array.Clear(c, 0, c.Length); } else if (!beta.IsOne()) { Control.LinearAlgebraProvider.ScaleArray(beta, c, c); } if (alpha.IsZero()) { return; } CacheObliviousMatrixMultiply(transposeA, transposeB, alpha, adata, 0, 0, bdata, 0, 0, c, 0, 0, m, n, k, m, n, k, true); }
/// <summary> /// Multiples two matrices. <c>result = x * y</c> /// </summary> /// <param name="x">The x matrix.</param> /// <param name="rowsX">The number of rows in the x matrix.</param> /// <param name="columnsX">The number of columns in the x matrix.</param> /// <param name="y">The y matrix.</param> /// <param name="rowsY">The number of rows in the y matrix.</param> /// <param name="columnsY">The number of columns in the y matrix.</param> /// <param name="result">Where to store the result of the multiplication.</param> /// <remarks>This is a simplified version of the BLAS GEMM routine with alpha /// set to 1.0 and beta set to 0.0, and x and y are not transposed.</remarks> public virtual void MatrixMultiply(Complex[] x, int rowsX, int columnsX, Complex[] y, int rowsY, int columnsY, Complex[] result) { // First check some basic requirement on the parameters of the matrix multiplication. if (x == null) { throw new ArgumentNullException("x"); } if (y == null) { throw new ArgumentNullException("y"); } if (result == null) { throw new ArgumentNullException("result"); } if (rowsX*columnsX != x.Length) { throw new ArgumentException("x.Length != xRows * xColumns"); } if (rowsY*columnsY != y.Length) { throw new ArgumentException("y.Length != yRows * yColumns"); } if (columnsX != rowsY) { throw new ArgumentException("xColumns != yRows"); } if (rowsX*columnsY != result.Length) { throw new ArgumentException("xRows * yColumns != result.Length"); } // Check whether we will be overwriting any of our inputs and make copies if necessary. // TODO - we can don't have to allocate a completely new matrix when x or y point to the same memory // as result, we can do it on a row wise basis. We should investigate this. Complex[] xdata; if (ReferenceEquals(x, result)) { xdata = (Complex[]) x.Clone(); } else { xdata = x; } Complex[] ydata; if (ReferenceEquals(y, result)) { ydata = (Complex[]) y.Clone(); } else { ydata = y; } MatrixMultiplyWithUpdate(Transpose.DontTranspose, Transpose.DontTranspose, Complex.One, xdata, rowsX, columnsX, ydata, rowsY, columnsY, Complex.Zero, result); }